TY - GEN
T1 - Learning with ensemble of linear perceptrons
AU - Hartono, Pitoyo
AU - Hashimoto, Shuji
PY - 2005
Y1 - 2005
N2 - In this paper we introduce a model of ensemble of linear perceptrons. The objective of the ensemble is to automatically divide the feature space into several regions and assign one ensemble member into each region and training the member to develop an expertise within the region. Utilizing the proposed ensemble model, the learning difficulty of each member can be reduced, thus achieving faster learning while guaranteeing the overall performance.
AB - In this paper we introduce a model of ensemble of linear perceptrons. The objective of the ensemble is to automatically divide the feature space into several regions and assign one ensemble member into each region and training the member to develop an expertise within the region. Utilizing the proposed ensemble model, the learning difficulty of each member can be reduced, thus achieving faster learning while guaranteeing the overall performance.
UR - http://www.scopus.com/inward/record.url?scp=33646259981&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33646259981&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33646259981
SN - 3540287558
SN - 9783540287551
VL - 3697 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 115
EP - 120
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005
Y2 - 11 September 2005 through 15 September 2005
ER -